Geometric camera calibration, or simply camera calibration, is used in several applications, notably in the field of computer vision, to allow three-dimensional (3D) metric information to be extracted from two-dimensional (2D) images. Non-limiting exemplary applications include image registration, object positioning, volumetric 3D reconstruction, dimensional measurements, gaming, augmented-reality environments, and photogrammetry. Camera calibration is a process of estimating the intrinsic and extrinsic camera parameters based on observations of a known physical target. The intrinsic parameters of a camera relate to the internal geometry and optical characteristics of the camera itself, while the extrinsic parameters measure the location and orientation of the camera with respect to a world coordinate system in 3D space.
Conventional camera calibration techniques use one or more images of a specifically designed calibration target or object. The calibration target includes several readily detectable fiducial markers or features with known relative 3D positions. By fixing the world coordinate system in the calibration object, point correspondences between 3D world points and 2D image points can be established. The intrinsic and extrinsic camera parameters can be computed by solving the system of equations resulting from these point correspondences.
Calibration methods can be divided into several categories. For example, according to the calibration object that they use, they can be classified into four categories: (i) 3D reference object based calibration, where camera calibration is performed by observing a calibration object whose geometry in 3D space is known with very good precision; (ii) 2D plane based calibration, where camera calibration involves the observation at different orientations of a planar calibration object having a calibration pattern thereon, but without requiring a priori knowledge of the 3D position of the calibration object at each orientation; (iii) one-dimensional (1D) based calibration, where the calibration objects are composed of a set of collinear points; and (iv) self-calibration, which does not use any calibration object.
Although various camera calibration techniques have been developed, numerous challenges remain, notably in terms of relieving the user from fastidious manual tasks, limiting the number of parameters and thresholds that need to be adjusted, allowing a real-time calibration to be performed, reducing calibration time; improving the ease of use for the user.